Biomedical research yields a wealth of information, much of which is only
accessible through the literature. Consequently, literature search is an
essential tool for building on prior knowledge in clinical and biomedical
research. Although recent improvements in artificial intelligence have expanded
functionality beyond keyword-based search, these advances may be unfamiliar to
clinicians and researchers. In response, we present a survey of literature
search tools tailored to both general and specific information needs in
biomedicine, with the objective of helping readers efficiently fulfill their
information needs. We first examine the widely used PubMed search engine,
discussing recent improvements and continued challenges. We then describe
literature search tools catering to five specific information needs: 1.
Identifying high-quality clinical research for evidence-based medicine. 2.
Retrieving gene-related information for precision medicine and genomics. 3.
Searching by meaning, including natural language questions. 4. Locating related
articles with literature recommendation. 5. Mining literature to discover
associations between concepts such as diseases and genetic variants.
Additionally, we cover practical considerations and best practices for choosing
and using these tools. Finally, we provide a perspective on the future of
literature search engines, considering recent breakthroughs in large language
models such as ChatGPT. In summary, our survey provides a comprehensive view of
biomedical literature search functionalities with 36 publicly available tools.

本研究调查了 36 种公开可用的工具，提供了有关医学文献搜索功能的全面视角，包括文献搜索、临床研究、基因相关信息、概念之间的关联等。